Research On Multi-Objective Path Planning For WCE With Joint Charging And Data Collection

In recent years,the wireless rechargeable sensor network has become a research hotspot.The existing research mainly focuses on the path planning for mobile wireless charging equipment(WCE).However,there are few studies on path planning for multi-functional WCE with joint charging and data collection.In general,the traveling path of the WCE is designed according to the charging requirements,and then the data collection strategy is considered.The impact of charging and data collection on path planning of the WCE is still not considered at the same time.This thesis simultaneously considers the impact of charging and data collection on the path planning of WCE.The path planning for the WCE with joint charging and data collection based on multi-objective optimization is studied.Aiming at the one to one charging and data collection for the WCE,the charging model and data collection model are established.The traveling energy and charging energy carried by the WCE are separate and limited.The path planning strategy for the WCE with joint charging and data collection is proposed.The design of the WCE path planning and the determination method of the WCE for node charging time are given.The multi-objective optimization problem is obtained with two objectives,maximizing the total energy utilization of the WCE and minimizing the average delay of node data transmission in the network.The one to one path planning algorithm for the WCE based on multi-objective ant colony optimization(OOP-MOACO)is designed to solve this problem.The experiments of 50 groups show that the highest total energy utilization of the WCE obtained by OOP-MOACO is 86.19%.Under the condition of the best average delay,the delay obtained by OOP-MOACO is 11.67%lower than that of NSGA-II.The average number of Pareto optimal solutions obtained by OOP-MOACO for solving this problem is 38.46%more than that of the NSGA-?.Furthermore,to deal with the one to many charging and data collection for WCE,the corresponding charging model and data collection model are established.The energy carried by the WCE is also separate and limited.In combination with the three cases resulting from charging sensor nodes in the virtual cellular grid,the path planning strategy for the WCE is proposed.The design of the path planning and the determination method of the WCE charging time based on virtual nodes are given.The multi-objective optimization problem is also obtained with two objectives,maximizing the total energy utilization of the WCE and minimizing the average delay of node data transmission in the network.The one to many path planning algorithm based on multi-objective ant colony optimization(OMP-MOACO)is designed to solve this problem.The comparative experiments show that that the highest WCE total energy utilization obtained by OMP-MOACO is 93.70%,meanwhile the average value is higher than that of NSGA-II.The optimal value of the average delay obtained by OMP-MOACO is 5.72%lower than that of NSGA-II.The average number of Pareto optimal solutions obtained by OMP-MOACO is increased by 80.95%compared with NSGA-II.